Static analysis for privacy-preserving artificial intelligence
In this talk, I will present the static analysis component of the open source Arcs Project, which is an ecosystem for building privacy-preserving AI applications . Specifically, I will talk about how we use static analysis to ensure that data is only used in approved ways in an AI application. First, I will introduce the Arcs programming model, the type system, and a policy specification language. Then, I will talk about how we use abstract interpretation and the guarantees provided by the type system to ensure that the application only uses data as outlined by the data-usage policy.
I am a staff engineer at Google, where I work on using formal methods for privacy preserving AI. Until recently, I was working as part of the exciting Swift for TensorFlow project. Previously, I led a team that develops static analysis tools to improve the security of Android Apps. Before that I was an engineer at Facebook, and a research staff member in the Systems Analysis and Verification (SAV) group at NEC Laboratories America, Inc. I got my Ph.D in from the University of Wisconsin-Madison.
Thu 19 NovDisplayed time zone: Central Time (US & Canada) change
17:00 - 18:20
|Static analysis for privacy-preserving artificial intelligenceInvited Talk|
I: Gogul Balakrishnan Google